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Models/ResUNet++ + TTA

ResUNet++ + TTA

Reported on 9 benchmarks across 1 task · 1 paper · 2 SOTA

Note: results are matched by exact model name. Different papers may use the same name for different model variants.

Medical9 results

  • Medical Image SegmentationonCVC-ColonDB
    mIoU· uses extra data· 2021-07-26
    0.8466
    best: 0.9096 (RAPUNet)
    SOTA
    A Comprehensive Study on Colorectal Polyp Segmentation with ResUNet++, Conditional Random Field and Test-Time AugmentationarXiv:2107.12435
  • Medical Image SegmentationonCVC-ColonDB
    mean Dice· uses extra data· 2021-07-26
    0.8474
    best: 0.9526 (RAPUNet)
    SOTA
    A Comprehensive Study on Colorectal Polyp Segmentation with ResUNet++, Conditional Random Field and Test-Time AugmentationarXiv:2107.12435
  • Medical Image SegmentationonETIS-LARIBPOLYPDB
    mIoU· 2021-07-26
    0.7458
    best: 0.9179 (RAPUNet)
    A Comprehensive Study on Colorectal Polyp Segmentation with ResUNet++, Conditional Random Field and Test-Time AugmentationarXiv:2107.12435
  • Medical Image SegmentationonETIS-LARIBPOLYPDB
    mean Dice· 2021-07-26
    0.6136
    best: 0.9572 (RAPUNet)
    A Comprehensive Study on Colorectal Polyp Segmentation with ResUNet++, Conditional Random Field and Test-Time AugmentationarXiv:2107.12435
  • Medical Image SegmentationonCVC-VideoClinicDB
    Dice· 2021-07-26
    0.8125
    best: 0.926 (Meta-Polyp)
    A Comprehensive Study on Colorectal Polyp Segmentation with ResUNet++, Conditional Random Field and Test-Time AugmentationarXiv:2107.12435
  • Medical Image SegmentationonCVC-VideoClinicDB
    Recall· 2021-07-26
    0.6896
    best: 0.7749 (ResUNet++)
    A Comprehensive Study on Colorectal Polyp Segmentation with ResUNet++, Conditional Random Field and Test-Time AugmentationarXiv:2107.12435
  • Medical Image SegmentationonCVC-VideoClinicDB
    mIoU· 2021-07-26
    0.8467
    best: 0.8739 (ResUNet++ + CRF)
    A Comprehensive Study on Colorectal Polyp Segmentation with ResUNet++, Conditional Random Field and Test-Time AugmentationarXiv:2107.12435
  • Medical Image SegmentationonCVC-VideoClinicDB
    precision· 2021-07-26
    0.6421
    best: 0.6706 (ResUNet++ + CRF)
    A Comprehensive Study on Colorectal Polyp Segmentation with ResUNet++, Conditional Random Field and Test-Time AugmentationarXiv:2107.12435
  • Medical Image SegmentationonCVC-ClinicDB
    mean Dice· 2021-07-26
    0.902
    best: 0.9684 (DUCK-Net)
    A Comprehensive Study on Colorectal Polyp Segmentation with ResUNet++, Conditional Random Field and Test-Time AugmentationarXiv:2107.12435